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FUJIFILM Synapse PACS Software is intended for use as a web-based application on an off-the shelf PC which meets or exceeds minimum specifications and is networked with a FUJIFILM Synapse PACS server.

The FUJIFILM Synapse PACS Software can process medical images from DICOM compliant modalities and non-DICOM sources.

FUJIFILM Synapse PACS Software provides toolsets for:

• Performing measurements on DICOM images
• Regional segmentation
• Importing and presenting data from modalities (DICOM and non-DICOM),
• Solving clinical calculations
• Creating and distributing structured reports

FUJIFILM Synapse PACS Software is intended to serve as the primary user interface for the processing of medical images for presentation on displays appropriate to the medical task being performed. It enables the display, comparison, fusion, and volume rendering of studies to aid in reading, interpreting, reporting, and treatment planning.

MIP, MPR Fusion, and volume rendering are not intended for mammography use. FUJIFILM Synapse PACS Software can be used to process FUJIFILM's DICOM MG "For Processing" images and also for the display, manipulation, and interpretation of lossless compressed or non-compressed mammography images that have been received in the DICOM For Presentation format and displayed on FDA-cleared, DICOM compatible displays for mammography.

The Synapse PACS is an enterprise-wide medical information and image management software that runs on standard "off-the-shelf" PC hardware and Software (OS, browser). Synapse is intended for communication, storage, display, manipulation, measurement, printing, and processing of images and information acquired from various medical imaging and information systems. As a Software as a Medical Device (SaMD), Synapse PACS performs these purposes without being part of a hardware medical device.

FUJIFILM Synapse PACS Software is intended for use as a web-based application on an off-the shelf PC which meets or exceeds minimum specifications and is networked with a FUJIFILM Synapse PACS server.

The FUJIFILM Synapse PACS Software can process medical images from DICOM compliant modalities and non-DICOM sources.

FUJIFILM Synapse PACS Software provides toolsets for:

• Performing measurements on DICOM images
• Regional segmentation
• Importing and presenting data from modalities (DICOM and non-DICOM),
• Solving clinical calculations
• Creating and distributing structured reports

Here's a breakdown of the acceptance criteria and study details for the Synapse PACS (7.5) device, based on the provided FDA 510(k) clearance letter:

Acceptance Criteria and Reported Device Performance

The core performance study described pertains to the Bone Removal algorithm.

1. A table of acceptance criteria and the reported device performance:

Note: The acceptance thresholds for DSC and 95% HD were determined by reviewing existing bone removal models in scientific literature.

Study Details Proving Device Meets Acceptance Criteria

2. Sample size used for the test set and the data provenance:

• Test Set Sample Size: 72 patients, each with one image collected.
• Data Provenance: The document states patient demographic distribution from "Midwest" (20 patients), "Southwest" (20 patients), and "Southeast" (32 patients) regions. This indicates the images were collected from various regions within the United States. The document does not explicitly state whether the data was retrospective or prospective, but the description of "collected images" and established ground truth often implies a retrospective study using an existing image archive.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Number of Experts: An initial bone mask was created by a "certified technologist." Then, an "independent dual-reader consensus review" was performed by two U.S. board-certified radiologists.
• Qualifications of Experts:
  • Certified Technologist (specific certification details not provided)
  • Two U.S. Board-Certified Radiologists (specific experience/years not provided, but "board-certified" implies a high level of qualification).

4. Adjudication method for the test set:

• Adjudication Method: A consensus review process was used. After an initial mask by a technologist, two U.S. board-certified radiologists independently evaluated the mask, recorded discrepancies, and iteratively reconciled them until consensus was achieved. This is a form of 2-reader independent reading with a consensus stage.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• No, an MRMC comparative effectiveness study was not performed as part of this submission's performance testing. The study focused on the standalone performance of the bone removal algorithm against a "definitive ground truth." The document does not describe human reader performance with or without the AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Yes, a standalone (algorithm only) performance study was conducted for the Bone Removal feature. The performance metrics (DSC and HD) directly measure the algorithm's output against the established ground truth.

7. The type of ground truth used:

• The ground truth used was expert consensus. Specifically, after an initial mask by a technologist, it was refined and finalized through an "independent dual-reader consensus review" by two U.S. board-certified radiologists.

8. The sample size for the training set:

• The provided document does not specify the sample size for the training set. It only describes the test set. It mentions the "Bone Removal is a tool that enhances the visibility of vessels... based on an AI algorithm cleared and marketed for Synapse 3D (K221677, reference device). It was improved for Synapse PACS 7.5.0." This implies the algorithm was already trained and validated prior to this submission, and this submission focuses on its performance after potential integration and improvements within Synapse PACS 7.5.0.

9. How the ground truth for the training set was established:

• The provided document does not describe how the ground truth for the training set (if applicable to this version's training) was established. Given that the algorithm was "improved" from a previously cleared device (Synapse 3D), the initial training and ground truth establishment would have occurred during the development and clearance process for that prior version.

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FUJIFILM Synapse PACS Software is intended for use as a web based application on an off-the shelf PC which meets or exceeds minimum specifications and is networked with a FUJIFILM Synapse PACS server.

The FUJIFILM Synapse PACS Software can process medical images from DICOM compliant modalities and non-DICOM sources.

The FUJIFILM Synapse PACS Software provides toolsets for performing measurements on DICOM images, importing and presenting data from modalities (DICOM and non-DICOM), solving clinical calculations, and creating and distributing structured reports.

The FUJIFILM Synapse PACS Software is intended to serve as the primary user interface for the processing of medical images for presentation on displays appropriate to the medical task being performed. It enables the display, comparison and fusion of 3D (MIP/MPR) of CT, MR, PET and SPECT studies.

Typical users are radiologists, cardiologists, technologists, sonographers, technicians, nurses and clinicians.

MIP, MPR, and Fusion are not intended for Mammography use. The FUJIFILM Synapse PACS Software may be used to process FUJIFILM's DICOM MG "For Processing" images and also for the display, manipulation, and interpretation of lossless compressed or non-compressed mammography images that have been received in the DICOM For Presentation format and displayed on FDA cleared, DICOM compatible displays for mammography.

The Synapse PACS which is the subject of this Premarket Notification Submission is a multipurpose, enterprise-wide application intended for communication, storage, display, printing, and processing of medical images. Its software components perform operations related to image manipulation and measurements relevant to radiology and cardiology. As a software-only device, it does not control image acquisition.

Typical users of Synapse PACs are radiologists, cardiologists, technologists, sonographers, technicians, nurses, and clinicians.

The software runs on standard PC equipment using MS Windows operating systems meeting minimum system requirements. An installed Synapse PACS system will typically be comprised of several Synapse PACS clients and one or more Synapse PACS servers

Synapse PACS accepts images and information from any DICOM-compliant acquisition device. In addition to system administrator tools, the device offers additional options for radiologist and cardiologist interpretation, in-house clinical review, and information access including reports, patient status, and clinical information acquired from various medical imaging and information systems.

This document is a 510(k) summary for the FUJIFILM Synapse PACS device. It describes the device, its intended use, and compares it to predicate devices to establish substantial equivalence.

Here's an analysis of the provided text in relation to acceptance criteria and study details:

Overall Conclusion based on the text:

The provided document (510(k) Summary) describes the FUJIFILM Synapse PACS as a Picture Archiving and Communication System (PACS). For devices like PACS, acceptance criteria typically revolve around functionality, performance, and cybersecurity, ensuring the system reliably stores, retrieves, displays, and processes medical images without compromising diagnostic integrity.

However, the provided text does not contain a specific study that quantifies device performance against specific acceptance criteria in the way typically expected for an AI/CADe device (e.g., sensitivity, specificity, AUC). Instead, the document establishes substantial equivalence by demonstrating that the Synapse PACS has the same general intended use, similar indications for use, principles of operation, and technological characteristics as its predicate devices, K160108 (Synapse PACS) and K151859 (Synapse Cardiovascular). The "study" here is primarily a comparative analysis against legally marketed devices, rather than a clinical performance study with predefined acceptance criteria and corresponding metrics.

The statement "Accepted methods for Verification and Validation testing were used for both the current and predicate devices. Software development and testing for both is in compliance with the IEC 62304 'Medical device software – Software life cycle processes' standard" implies that standard software V&V processes were followed, which would include testing against functional and performance specifications. However, the specific results of these tests are not detailed in this summary.

Given this, I will populate the table and answer the questions based on the information that is available in the provided 510(k) summary, and note where information is not present.

1. Table of acceptance criteria and the reported device performance:

Based on the provided text, the following information is NOT available:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Not mentioned. The document refers to "Verification and Validation testing" but does not detail any specific test sets, sample sizes, or data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• Not mentioned. Since specific test sets are not detailed, there is no information about experts establishing ground truth.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• Not mentioned.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• Not done/Not mentioned. This device is a PACS, not an AI/CADe device designed to assist human readers directly in diagnosis to improve their performance. Therefore, an MRMC study comparing human reader performance with and without AI assistance is not described or relevant for this submission type.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Not applicable/Not mentioned. The Synapse PACS is a system for image management and display, not a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

• Not mentioned.

8. The sample size for the training set

• Not applicable/Not mentioned. This is a PACS system, not a machine learning algorithm that requires a "training set" in the conventional sense. Its "training" would be its software development and testing, compliant with IEC 62304.

9. How the ground truth for the training set was established

• Not applicable/Not mentioned. See point 8.

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FUJIFILM Synapse PACS Software (client) is intended for use, as a web based application, on an off-the-shelf PC meeting or exceeding minimum specifications and networked with FUJIFILM Synapse PACS Software (Server). The FUJIFILM Synapse PACS Software is intended to serve as the primary user interface for the processing of medical images for presentation on displays appropriate to the medical task being performed. The Synapse PACS Software can process medical images from the following modality types: plane X-ray radiography, X-ray computed tomography, magnetic resonance imaging, ultrasound, nuclear medicine and images from other DICOM compliant modalities.

The FUJIFILM Synapse PACS Software enables the display, comparison of 3D (MIP/MPR) of CT, MR, PET and SPECT studies. Typical users are radiologists and clinicians. These functions (MIPMPR/Fusion) are not intended for Mammography use.

The FUJIFILM Synapse PACS Software may be used to process FUJIFILM's DICOM MG "For Processing" images and also for the display, manipulation, and interpretation of lossless compressed mammography images that have been received in the DICOM For Presentation format and displayed on FDA cleared, DICOM compatible displays for mammography.

The proposed Synapse PACS Software is an implementation that combines capabilities of Synapse Workstation software (K112439) and Synapse MPR/Fusion software (K113244) in a single system, using the current Internet standards for Web clients and servers. The Synapse PACS Software and the predicate devices, i.e., Synapse Workstation Software (K112439) and Synapse MPR Fusion Software (K113244), are picture archiving and communication systems (as defined by 21 CFR 892.2050). Synapse PACS Software is the web based (client/server) application and implementation of the Synapse Workstation Software and the Synapse MPR Fusion Software. The Synapse PACS Software (client) is intended for use, as a web based application, on an off-the-shelf PC meeting or exceeding minimum specifications and networked with Synapse PACS Software (server). The Synapse PACS Software is intended to serve as the primary user interface for the processing of medical images for presentation on displays appropriate to the medical task being performed. The Synapse PACS Software can process medical images from the following modality types: plane X-ray radiography, X-ray computed tomography, magnetic resonance imaging, ultrasound, nuclear medicine and images from other DICOM compliant modalities. Synapse PACS Software enables the display, comparison and fusion of 3D (MIP/MPR) of CT, MR, PET and SPECT studies (K113244).

In summary, this 510(k) submission introduces the Synapse PACS with the web based (client/server) application and the ability to the display, comparison and fusion of 3D (MIP/MPR) of CT, MR, PET and SPECT studies.

The provided text is a 510(k) summary for the FUJIFILM Synapse PACS (K160108). This document primarily focuses on establishing substantial equivalence to previously cleared predicate devices (Synapse Workstation K112439 and Synapse MPR Fusion K113244) rather than presenting a performance study with detailed acceptance criteria and testing methodology for a novel diagnostic algorithm.

The document describes the device, its intended use, and provides comparisons of features, technology, and specifications with the predicate devices. It also mentions general testing activities. However, it does not detail a specific study proving the device meets acceptance criteria in the way one would for a new AI/CAD device. The Synapse PACS is a picture archiving and communication system, and its "performance" is more related to its functionality, speed, and ability to display and process images, rather than the diagnostic accuracy of an interpretation algorithm.

Therefore, many of the requested elements for describing a study proving the device meets acceptance criteria for a diagnostic AI/CAD device are not applicable or not detailed in this 510(k) summary.

Here's an attempt to answer the questions based on the provided text, indicating where information is not present:

Acceptance Criteria and Study for FUJIFILM Synapse PACS (K160108)

This 510(k) submission for the Synapse PACS focuses on demonstrating substantial equivalence to predicate devices for its functionalities as a PACS system, not on proving diagnostic performance of a new AI algorithm. Therefore, the "acceptance criteria" and "study" described below are interpreted in the context of a PACS system's performance and equivalence, rather than the accuracy of an automated diagnostic output.

1. Table of Acceptance Criteria and Reported Device Performance

For a PACS system, acceptance criteria are generally related to its functionality, performance (speed, responsiveness), and ability to display and process images as intended. The document states "Pass/Fail criteria were based on the requirements and intended use of the product. Test results showed that all tests successfully passed." Specific quantitative criteria are not listed for individual functions.

2. Sample Size Used for the Test Set and Data Provenance

The document mentions "actual clinical images" were used for "benchmark performance testing" but does not specify the sample size or their provenance (e.g., country of origin, retrospective/prospective collection). Given the nature of a PACS system, the "test set" would likely be a diverse range of images to ensure format compatibility and display accuracy across modalities, rather than a specific set for diagnostic accuracy assessment.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Not applicable. For a PACS system, "ground truth" in the diagnostic sense is not typically established by experts as the system's function is to display and process, not to provide diagnostic interpretations. The ground truth for its performance would be whether it accurately displays images, performs requested manipulations, and stores/retrieves data correctly. This would be verified through technical testing and potentially user acceptance testing by radiologists/clinicians, but not in the same way as establishing ground truth for an AI diagnostic algorithm.

4. Adjudication Method for the Test Set

Not applicable. Adjudication methods (e.g., 2+1, 3+1) are used to resolve discrepancies among expert readers when establishing ground truth for diagnostic studies. This is not relevant to the functional validation of a PACS system.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No. An MRMC study is typically performed to evaluate the impact of an AI algorithm on human reader performance (e.g., improved diagnostic accuracy, reduced reading time). This device is a PACS system, not a diagnostic AI algorithm, so such a study would not be applicable or expected.

6. If a Standalone (i.e. algorithm only without human-in-the loop performance) was done

Not applicable. This device is a PACS system, which is a tool for human interpretation and management of medical images. It does not perform standalone diagnostic interpretations.

7. The Type of Ground Truth Used

The "ground truth" for a PACS system would be the technical specifications and clinical expectations for image display, processing, and storage. For example:

• Technical Specifications: Does the system accurately render images according to DICOM standards? Are measurements correct?
• Functional Expectations: Does it perform MIP/MPR as specified? Does it retrieve images within an acceptable timeframe?
  These are assessed through verification and validation testing, not typically through pathology, expert consensus, or outcomes data in the diagnostic sense. The document refers to "benchmark performance testing using actual clinical images," which suggests an evaluation against expected display and processing quality for real-world data.

8. The Sample Size for the Training Set

Not applicable. PACS software, like the Synapse PACS, is developed based on software engineering principles and medical imaging standards (e.g., DICOM). It does not use "training sets" in the machine learning sense to learn to perform a task. It is a rule-based system designed to display and manage images.

9. How the Ground Truth for the Training Set was Established

Not applicable, as there is no "training set" for a PACS system in this context.

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